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AI finds different recipes for carbon nanotube forests with matching structures
An AI-assisted inverse-design framework has identified multiple distinct growth recipes that reach the same prescribed height, density and alignment in carbon nanotube forests. Trained on 200 water-assisted chemical vapour deposition experiments, the model searched backward from structural targets; 26 of 27 validation batches scored above 95% descriptor matching, yet nanotube diameters and wall structures differed.
6 days ago2 min read
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